Об этом курсе
4.2
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Рецензии: 76
How can robots determine their state and properties of the surrounding environment from noisy sensor measurements in time? In this module you will learn how to get robots to incorporate uncertainty into estimating and learning from a dynamic and changing world. Specific topics that will be covered include probabilistic generative models, Bayesian filtering for localization and mapping....
Stacks

Course 5 of 6 in the

специализации ''Robotics''
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Approx. 12 hours to complete

Предполагаемая нагрузка: 4 weeks of study, 3-4 hours/week...
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Субтитры: English, Chinese (Simplified)...

Приобретаемые навыки

Particle FilterEstimationMapping
Stacks

Course 5 of 6 in the

специализации ''Robotics''
Globe

Только онлайн-курсы

Начните сейчас и учитесь по собственному графику.
Calendar

Гибкие сроки

Назначьте сроки сдачи в соответствии со своим графиком.
Clock

Approx. 12 hours to complete

Предполагаемая нагрузка: 4 weeks of study, 3-4 hours/week...
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English

Субтитры: English, Chinese (Simplified)...

Программа курса: что вы изучите

Week
1
Clock
4 ч. на завершение

Gaussian Model Learning

We will learn about the Gaussian distribution for parametric modeling in robotics. The Gaussian distribution is the most widely used continuous distribution and provides a useful way to estimate uncertainty and predict in the world. We will start by discussing the one-dimensional Gaussian distribution, and then move on to the multivariate Gaussian distribution. Finally, we will extend the concept to models that use Mixtures of Gaussians....
Reading
9 видео (всего 52 мин.), 3 материалов для самостоятельного изучения, 1 тест
Video9 видео
Course Introduction3мин
WEEK 1 Introduction1мин
1.2.1. 1D Gaussian Distribution8мин
1.2.2. Maximum Likelihood Estimate (MLE)6мин
1.3.1. Multivariate Gaussian Distribution7мин
1.3.2. MLE of Multivariate Gaussian4мин
1.4.1. Gaussian Mixture Model (GMM)4мин
1.4.2. GMM Parameter Estimation via EM7мин
1.4.3. Expectation-Maximization (EM)6мин
Reading3 материала для самостоятельного изучения
MATLAB Tutorial - Getting Started with MATLAB10мин
Setting Up your MATLAB Environment10мин
Basic Probability10мин
Week
2
Clock
3 ч. на завершение

Bayesian Estimation - Target Tracking

We will learn about the Gaussian distribution for tracking a dynamical system. We will start by discussing the dynamical systems and their impact on probability distributions. This linear Kalman filter system will be described in detail, and, in addition, non-linear filtering systems will be explored....
Reading
5 видео (всего 21 мин.), 1 тест
Video5 видео
WEEK 2 Introduction1мин
Kalman Filter Motivation4мин
System and Measurement Models5мин
Maximum-A-Posterior Estimation4мин
Extended Kalman Filter and Unscented Kalman Filter4мин
Week
3
Clock
4 ч. на завершение

Mapping

We will learn about robotic mapping. Specifically, our goal of this week is to understand a mapping algorithm called Occupancy Grid Mapping based on range measurements. Later in the week, we introduce 3D mapping as well....
Reading
6 видео (всего 36 мин.), 1 тест
Video6 видео
WEEK 3 Introduction1мин
Introduction to Mapping7мин
3.2.1. Occupancy Grid Map6мин
3.2.2. Log-odd Update6мин
3.2.3. Handling Range Sensor6мин
Introduction to 3D Mapping8мин
Week
4
Clock
3 ч. на завершение

Bayesian Estimation - Localization

We will learn about robotic localization. Specifically, our goal of this week is to understand a how range measurements, coupled with odometer readings, can place a robot on a map. Later in the week, we introduce 3D localization as well....
Reading
6 видео (всего 23 мин.), 1 тест
Video6 видео
WEEK 4 Introduction1мин
Odometry Modeling5мин
Map Registration5мин
Particle Filter4мин
Iterative Closest Point5мин
Closingмин
4.2
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Лучшие рецензии

автор: VG•Feb 16th 2017

The material is clearly presented. The Matlab exercises complement and reinforce the subject, the level of difficulty is well balanced, thanks for this great course.

автор: NN•Jun 20th 2016

This is course is really helpful for beginners to understand how probability is useful in Robotics.Assignments are bit tough but worth the time .

Преподаватель

Daniel Lee

Professor of Electrical and Systems Engineering
School of Engineering and Applied Science

О University of Pennsylvania

The University of Pennsylvania (commonly referred to as Penn) is a private university, located in Philadelphia, Pennsylvania, United States. A member of the Ivy League, Penn is the fourth-oldest institution of higher education in the United States, and considers itself to be the first university in the United States with both undergraduate and graduate studies. ...

О специализации ''Robotics'

The Introduction to Robotics Specialization introduces you to the concepts of robot flight and movement, how robots perceive their environment, and how they adjust their movements to avoid obstacles, navigate difficult terrains and accomplish complex tasks such as construction and disaster recovery. You will be exposed to real world examples of how robots have been applied in disaster situations, how they have made advances in human health care and what their future capabilities will be. The courses build towards a capstone in which you will learn how to program a robot to perform a variety of movements such as flying and grasping objects....
Robotics

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